Modern wireless communication systems employ spectrally efficient, digitally modulated signals with wide bandwidths and time-varying envelopes. Such systems are very sensitive to different sources of linear and nonlinear distortions that may be exhibited by the radio frequency (RF) transmitters, especially the power amplifier (PA) stage. Hence, RF transmitters have to meet strict linearity requirements in order to avoid the signal quality deterioration and adjacent channel interference. At the same time, RF transmitters must be efficient in order to comply with low power requirements of wireless communication systems.
Amplifier nonlinearities may cause several complications in the wireless digital system and significantly complicate design of such systems. For example, they may produce a dilation/spreading of the spectrum of the input signal, which may cause adjacent channel interference. In addition to such spectral regrowth, amplifier nonlinearities may produce in-band distortions which deteriorate the integrity of the transmitted signal. The minimization of the effects of such distortion sources relies primary on accurate modeling of the RF transmitters.
There are several prior art models of dynamic nonlinear systems. However, one common problem of such models is in the identification procedure of the parameters of their different modules. Furthermore, the known models and procedures encounter high complexity and/or low accuracy. Moreover, they frequently do not account for the strong memory effects exhibited by the transmitter/PA. Thus, in most cases, they are not appropriate for implementation in broadband adaptive communications systems. Accordingly, there is a need for a new dynamic nonlinear system model that overcomes limitations of the prior art behavioral models.